{"title":"光污染综合评价研究","authors":"Yongchen Zhao","doi":"10.54254/2755-2721/59/20240757","DOIUrl":null,"url":null,"abstract":"Light pollution refers to the inappropriate and excessive use of artificial light. The increasing extent and intensity of artificial light has impacted the biology and ecology of species significantly. Admittedly, the widespread use of light benefits people to a large extent and is positively associated with modernization, security, and wealth. But its catastrophic effects can never be ignored. To be specific, light pollution can arouse negative health impacts such as headaches, dizziness, increased anxiety, pressure, and fatigue. The paper wants to find applicable indicators regarding the risk levels of light pollution and establish criteria to judge the risk of light pollution in different areas. In the process, the research first measures the interconnection between the indicators, which are chosen to reflect the risk of light pollution, and then uses PCA to implement dimensionality reduction so as to simplify the model. After that, EWM and TOPSIS are applied to determine the weight of each indicator and the rating of the cities. Institutions or governments that are responsible for managing light pollution can then use the model to judge the risk level of different cities. The model can help to avoid overlooking or overemphasizing a city's light pollution risk level, providing a more accurate estimation. In this case, institutions and the government can take better and more effective measures to restrict light pollution.","PeriodicalId":350976,"journal":{"name":"Applied and Computational Engineering","volume":"138 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on the comprehensive evaluation of light pollution\",\"authors\":\"Yongchen Zhao\",\"doi\":\"10.54254/2755-2721/59/20240757\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Light pollution refers to the inappropriate and excessive use of artificial light. The increasing extent and intensity of artificial light has impacted the biology and ecology of species significantly. Admittedly, the widespread use of light benefits people to a large extent and is positively associated with modernization, security, and wealth. But its catastrophic effects can never be ignored. To be specific, light pollution can arouse negative health impacts such as headaches, dizziness, increased anxiety, pressure, and fatigue. The paper wants to find applicable indicators regarding the risk levels of light pollution and establish criteria to judge the risk of light pollution in different areas. In the process, the research first measures the interconnection between the indicators, which are chosen to reflect the risk of light pollution, and then uses PCA to implement dimensionality reduction so as to simplify the model. After that, EWM and TOPSIS are applied to determine the weight of each indicator and the rating of the cities. Institutions or governments that are responsible for managing light pollution can then use the model to judge the risk level of different cities. The model can help to avoid overlooking or overemphasizing a city's light pollution risk level, providing a more accurate estimation. In this case, institutions and the government can take better and more effective measures to restrict light pollution.\",\"PeriodicalId\":350976,\"journal\":{\"name\":\"Applied and Computational Engineering\",\"volume\":\"138 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied and Computational Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54254/2755-2721/59/20240757\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied and Computational Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54254/2755-2721/59/20240757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on the comprehensive evaluation of light pollution
Light pollution refers to the inappropriate and excessive use of artificial light. The increasing extent and intensity of artificial light has impacted the biology and ecology of species significantly. Admittedly, the widespread use of light benefits people to a large extent and is positively associated with modernization, security, and wealth. But its catastrophic effects can never be ignored. To be specific, light pollution can arouse negative health impacts such as headaches, dizziness, increased anxiety, pressure, and fatigue. The paper wants to find applicable indicators regarding the risk levels of light pollution and establish criteria to judge the risk of light pollution in different areas. In the process, the research first measures the interconnection between the indicators, which are chosen to reflect the risk of light pollution, and then uses PCA to implement dimensionality reduction so as to simplify the model. After that, EWM and TOPSIS are applied to determine the weight of each indicator and the rating of the cities. Institutions or governments that are responsible for managing light pollution can then use the model to judge the risk level of different cities. The model can help to avoid overlooking or overemphasizing a city's light pollution risk level, providing a more accurate estimation. In this case, institutions and the government can take better and more effective measures to restrict light pollution.